1. Field of the Invention
This invention relates to a computer-implemented data mining system, and in particular, to a system for analyzing retail transactions using Gaussian Mixture Models in a distributed relational data mining system.
2. Description of Related Art
Many computer-implemented systems are used to analyze commercial and financial transaction data. In many instances, such data is analyzed to gain a better understanding of customer behavior by analysis of customer transactions.
Prior art methods for analyzing customer transactions often involve one or more of the following techniques:
1. Ad hoc querying: This methodology involves the iterative analysis of transaction data by human effort, using querying languages such as SQL.
2. On-line Analytical Processing (OLAP): This methodology involves the application of automated software front-ends that automate the querying of relational databases storing transaction data and the production of reports therefrom.
3. Statistical packages: This methodology requires the sampling of transaction data, the extraction of the data into flat file or other proprietary formats, and the application of general purpose statistical or data mining software packages to the data.
Nonetheless, there remains a need for improved techniques for analyzing transaction data.